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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Towards Human-Friendly Efficient Control of Multi-Robot Teams

This paper explores means to increase efficiency in performing tasks with multi-robot teams, in the context of natural Human-Multi-Robot Interfaces (HMRI) for command and control. The motivating scenario is an emergency evacuation by a transport convoy of unmanned ground vehicles (UGVs) that have to traverse, in shortest time, an unknown terrain. In the experiments the operator commands, in minimal time, a group of rovers through a maze. The efficiency of performing such tasks depends on both, the levels of robots' autonomy, and the ability of the operator to command and control the team. The paper extends the classic framework of levels of autonomy (LOA), to levels/hierarchy of autonomy characteristic of Groups (G-LOA), and uses it to determine new strategies for control. An UGVoriented command language (UGVL) is defined, and a mapping is performed from the human-friendly gesture-based HMRI into the UGVL. The UGVL is used to control a team of 3 robots, exploring the efficiency of different G-LOA; specifically, by (a) controlling each robot individually through the maze, (b) controlling a leader and cloning its controls to followers, and (c) controlling the entire group. Not surprisingly, commands at increased G-LOA lead to a faster traverse, yet a number of aspects are worth discussing in this context.

multi-robot control↗
NASA NTRS2010

Risk Identification and Visualization in a Concurrent Engineering Team Environment

Incorporating risk assessment into the dynamic environment of a concurrent engineering team requires rapid response and adaptation. Generating consistent risk lists with inputs from all the relevant subsystems and presenting the results clearly to the stakeholders in a concurrent engineering environment is difficult because of the speed with which decisions are made. In this paper we describe the various approaches and techniques that have been explored for the point designs of JPL's Team X and the Trade Space Studies of the Rapid Mission Architecture Team. The paper will also focus on the issues of the misuse of categorical and ordinal data that keep arising within current engineering risk approaches and also in the applied risk literature.

Risk Scoring↗
NASA NTRS2013

Dawn Orbit Determination Team: Trajectory and Gravity Prediction Performance During Vesta Science Phases

The Dawn spacecraft was launched on September 27th, 2007. Its mission is to consecutively rendezvous with and observe the two largest bodies in the asteroid belt, Vesta and Ceres. It has already completed over a year's worth of direct observations of Vesta (spanning from early 2011 through late 2012) and is currently on a cruise trajectory to Ceres, where it will begin scientific observations in mid-2015. Achieving this data collection required careful planning and execution from all spacecraft teams. Dawn's Orbit Determination (OD) team was tasked with accurately predicting the trajectory of the Dawn spacecraft during the Vesta science phases, and also determining the parameters of Vesta to support future science orbit design. The future orbits included the upcoming science phase orbits as well as the transfer orbits between science phases. In all, five science phases were executed at Vesta, and this paper will describe some of the OD team contributions to the planning and execution of those phases.

gravity gradient torque↗
NASA NTRS2015

A Metric to Quantify Shared Visual Attention in Two-Person Teams

Introduction: Critical tasks in high-risk environments are often performed by teams, the members of which must work together efficiently. In some situations, the team members may have to work together to solve a particular problem, while in others it may be better for them to divide the work into separate tasks that can be completed in parallel. We hypothesize that these two team strategies can be differentiated on the basis of shared visual attention, measured by gaze tracking. 2) Methods: Gaze recordings were obtained for two-person flight crews flying a high-fidelity simulator (Gontar, Hoermann, 2014). Gaze was categorized with respect to 12 areas of interest (AOIs). We used these data to construct time series of 12 dimensional vectors, with each vector component representing one of the AOIs. At each time step, each vector component was set to 0, except for the one corresponding to the currently fixated AOI, which was set to 1. This time series could then be averaged in time, with the averaging window time (t) as a variable parameter. For example, when we average with a t of one minute, each vector component represents the proportion of time that the corresponding AOI was fixated within the corresponding one minute interval. We then computed the Pearson product-moment correlation coefficient between the gaze proportion vectors for each of the two crew members, at each point in time, resulting in a signal representing the time-varying correlation between gaze behaviors. We determined criteria for concluding correlated gaze behavior using two methods: first, a permutation test was applied to the subjects' data. When one crew member's gaze proportion vector is correlated with a random time sample from the other crewmember's data, a distribution of correlation values is obtained that differs markedly from the distribution obtained from temporally aligned samples. In addition to validating that the gaze tracker was functioning reasonably well, this also allows us to compute probabilities of coordinated behavior for each value of the correlation. As an alternative, we also tabulated distributions of correlation coefficients for synthetic data sets, in which the behavior was modeled as a first-order Markov process, and compared correlation distributions for identical processes with those for disparate processes, allowing us to choose criteria and estimate error rates. 3) Discussion: Our method of gaze correlation is able to measure shared visual attention, and can distinguish between activities involving different instruments. We plan to analyze whether pilots strategies of sharing visual attention can predict performance. Possible measurements of performance include expert ratings from instructors, fuel consumption, total task time, and failure rate. While developed for two-person crews, our approach can be applied to larger groups, using intra-class correlation coefficients instead of the Pearson product-moment correlation.

Gontar, Patrick↗
NASA NTRS2015

A Metric to Quantify Shared Visual Attention in Two-Person Teams

Critical tasks in high-risk environments are often performed by teams, the members of which must work together efficiently. In some situations, the team members may have to work together to solve a particular problem, while in others it may be better for them to divide the work into separate tasks that can be completed in parallel. We hypothesize that these two team strategies can be differentiated on the basis of shared visual attention, measured by gaze tracking.

Gontar, Patrick↗
NASA NTRS2016

Final Report of the NASA Technology Readiness Assessment (TRA) Study Team

The material in this report covers the results on the NASA-wide TRA team, who are responsible for ascertaining the full extent of issues and ambiguities pertaining to TRATRL and to provide recommendations for mitigation. The team worked for approximately 6 months to become knowledgeable on the current TRATRL process and guidance and to derive recommendations for improvement.The team reviewed the TRA processes of other government agencies (OGA), including international agencies, and found that while the high-level processes are similar, the NASA process has a greater level of detail. Finally, NASA’s HQ OCT continues to monitor the GAO’s efforts to produce a TRA Best Practices Guide, a draft of which was received in February 2016. This Guide could impact the recommendations of this report.

Technology readiness assessment↗
NASA NTRS2017

Introduction to the Navigation Team: Johnson Space Center EG6 Internship

The EG6 navigation team at NASA Johnson Space Center, like any team of engineers, interacts with the engineering process from beginning to end; from exploring solutions to a problem, to prototyping and studying the implementations, all the way to polishing and verifying a final flight-ready design. This summer, I was privileged enough to gain exposure to each of these processes, while also getting to truly experience working within a team of engineers. My summer can be broken up into three projects: i) Initial study and prototyping: investigating a manual navigation method that can be utilized onboard Orion in the event of catastrophic failure of navigation systems; ii) Finalizing and verifying code: altering a software routine to improve its robustness and reliability, as well as designing unit tests to verify its performance; and iii) Development of testing equipment: assisting in developing and integrating of a high-fidelity testbed to verify the performance of software and hardware.

Gualdoni, Matthew↗
NASA NTRS2017

WCRP Task Team for the Intercomparison of Reanalyses (TIRA): Motivation and Progress

Reanalyses have proven to be an important resource for weather and climate related research, as well as societal applications at large. Several centers have emerged to produce new atmospheric reanalyses in various forms every few years. In addition, land and ocean communities are producing disciplinary uncoupled reanalyses. Current research and development in reanalysis is directed at (1) extending the length of reanalyzed period and (2) use of coupled Earth system models for climate reanalysis. While WCRPs involvement in the reanalyses communities through its Data Advisory Council (WDAC) has been substantial, for example in organizing international conferences on reanalyses, a central team of reanalyses expertise is not in place in the WCRP structure. The differences among reanalyses and their inherent uncertainties are some of the most important questions for both users and developers of reanalyses. Therefore, a collaborative effort to systematically assess and intercompare reanalyses would be a logical progression that fills the needs of the community and contributes to the WCRP mission. The primary charge to the TIRA is to develop a reanalysis intercomparison project plan that will attain the following objectives.1)To foster understanding and estimation of uncertainties in reanalysis data by intercomparison and other means 2)To communicate new developments and best practices among the reanalyses producing centers 3)To enhance the understanding of data and assimilation issues and their impact on uncertainties, leading to improved reanalyses for climate assessment 4)To communicate the strengths and weaknesses of reanalyses, their fitness for purpose, and best practices in the use of reanalysis datasets by the scientific community. This presentation outlines the need for a task team on reanalyses, their intercomparison, the objectives of the team and progress thus far.

WDA↗
NASA NTRS2016

Independent Navigation Team Contribution to New Horizons' Pluto System Flyby

The New Horizons spacecraft made it closest approach to Pluto on 14 July 2015. The most significant challenge of this mission was that the Pluto system ephemeris was initially known with a precision of ~1000 km. This needed to be improved significantly on approach in order to meet the science requirements. During the final six months leading to the flyby, a JPL Independent Navigation (INAV) Team was included in the ephemeris knowledge update process as a cross-check on the Project Navigation (PNAV) Team's results. This paper discusses the INAV team's experiences and challenges navigating New Horizons through the Pluto planetary system encounter.

orbit determination↗
NASA NTRS2019

Mission Operations Working Group (MOWG) Report to the Aura Science Team

This presentation provides mission operations status for the Earth Observing System (EOS) Aura satellite to the Aura Science Team community. It is a summary of the splinter meeting held between the Aura Flight Operations Team (FOT) and the Instrument Operations Teams (IOT). The material covers highlights of activities, any significant issues or concerns, and future plans of the mission and instruments.

Fisher, Dominic M.↗
NASA NTRS2019

Advancing Aircraft Operations in a Net-Centric Environment with the Incorporation of Increasingly Autonomous Systems and Human Teaming

NextGen has begun the modernization of the nation’s air transportation system, with goals to improve system safety, increase operation efficiency and capacity, provide enhanced predictability, resilience and robustness. With these improvements, NextGen is poised to handle significant increases in air traffic operations, more than twice the number recorded in 2016, by 2025.1 NextGen is evolving toward collaborative decision-making across many agents, including automation, by use of a Net-Centric architecture, which in itself creates a very complex environment in which the navigation and operation of aircraft are to take place. An intricate environment such as this, coupled with the expected upsurge of air traffic operations generates concern respecting the ability of the human-agent to both fly and manage aircraft within. Therefore, it is both necessary and practical to begin the process of increasingly autonomous systems within the cockpit that will act independently to assist the human-agent achieve the overall goal of NextGen. However, the straightforward technological development and implementation of intelligent machines into the cockpit is only part of what is necessary to maintain, at minimum, or improve human-agent functionality, as desired, while operating in NextGen. The full integration of Increasingly Autonomous Systems (IAS) within the cockpit can only be accomplished when the IAS works in concert with the human, formulating trust between the two, thereby establishing a team atmosphere. Imperative to cockpit implementation is ensuring the proper performance of the IAS by the development team and the human-agent with which it will be paired when given a specific piloting, navigation, or observational task. Described in this paper are the steps taken, at NASA Langley Research Center, during the second and third phases of the development of an IAS, the Traffic Data Manager (TDM), its verification and validation by human-agents, and the foundational development of Human Autonomy Teaming (HAT) between the two.

Houston, Vincent E.↗
NASA NTRSDate not supplied

Analyzing Natural Language Context in Human-Machine Teaming using Supervised Machine Learning

Building a foundation for trustworthiness and trust verification in multi-asset teaming is the research challenge of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Design Reference Mission (DRM) for ATTRACTOR is a search and rescue mission objective governed by a multi-member team consisting of human and machine operators. A crucial component to the effort is the communication between humans and autonomous agents throughout both planning and execution stages of the mission. Intuitive communication methods and modalities are posited as critical enablers for certifying trust and trustworthiness. This paper reports on the data collection and analysis conducted in support of the Human Informed Natural-language GANs Evaluation (HINGE)project to attain explainable and trusted communication between human-machine assets. Two identically curated image description datasets were acquired for HINGE, both consisting of two unique input modalities (typed vs. verbal) and retrieved in two distinct contexts (general vs. specific). The gathered datasets were assessed and compared using Parts-of-Speech (POS)features, sentence similarity metrics, and linguistic analysis. Then, the datasets were modeled and tested separately and in combination with one another using machine learning algorithms. The comparison and testing results reveal a superior dataset, by which a preferred context and input is understood, for generating image representations of missing persons using a Generative Adversarial Network (GAN).

Bryan A Barrows↗
NASA NTRSDate not supplied

Enabling Advanced Air Mobility Operations through Appropriate Trust in Human-Autonomy Teaming: Foundational Research Approaches and Applications

Emerging Advanced Air Mobility(AAM)operations will be enabled by increasingly autonomous systems, requiring technologies to take on more responsibilities and fundamentally altering traditional human-automation interaction paradigms. The growing reliance on higher levels of automation will necessitate research to identify capabilities and principles that facilitate humans and machines working and thinking better together, i.e., human-autonomy teaming (HAT). Trust is an inherent requirement in effective teams because when members work interdependently, those agents (human, automation) must be willing to accept a level of risk to rely upon each other to reach goals and contribute to team tasks. This work provides an initial approach to enabling AAM operations through appropriate trust within HAT. The main contributions of this approach resides in connecting the construct of trust to mental models. Using the outlined mental model approach, we propose novel HAT strategies, such as Adaptive Trust Calibration, and preview planned research activities derived from this approach. Additionally, we propose several practical applications that can currently be employed by AAM development communities.

Eric T Chancey↗
NASA NTRSDate not supplied

Intercenter Systems Analysis Team (ISAT) Overview

This presentation provides an overview of the Intercenter Systems Analysis Team (ISAT). It summarizes the team mission, types of studies conducted by the team, and the members.

Systems Analysis↗
NASA NTRS2021

NASA Academy Summer 2021 Equipment Development Team Report

Wildfires have become increasingly frequent, widespread, intense, and destructive. The 2021 NASA Academy at Langley Research Center was given the task of applying NASA technology to the challenges faced by wildland firefighting professionals. The Equipment Development Team focused on developing tools that could be deployed to make the work of wildland firefighters safer and more effective. The team developed both a conceptual design and a prototype of a lightweight respirator with air cooling capabilities. The team also researched body-worn biometric and environmental sensors, identifying a suite of sensors that could predict and alert firefighters to dangerous physical and environmental conditions. This report outlines the results of these activities, and analyzes each component of the systems, identifying challenges, possible technological solutions, and their feasibility.

Kilarendha Sundling↗
NASA NTRS2022

Lithological variation of asteroid Ryugu samples returned by the Hayabusa 2 spacecraft: Assessment from the 18 particles distributed to the initial analysis “Stone” team

JAXA’s Hayabusa2 spacecraft successfully returned~5.4g of C-type asteroid Ryugu materials on Dec. 2020 [e.g., 1] and the recovered samples were extensively analyzed by initial analysis teams and Phase2 curation teams. The reported results show that Ryugu samples are similar to CI chondritesin chemistry and mineralogy, showing evidence for aqueous alteration in the parent body [e.g., 2,3]. As a “stone” team of the initial analysis, we received 18coarse particles (>1 mm) of Ryugu samples to characterize their mineralogy and petrology. We found that the samples were breccias of mm-to-sub mm size clasts. All of the clasts are mainly composed of Mg-Fe phyllosilicates, but the alteration degree appears slightly different from one clast to another. Here we report a lithological variation of Ryugu samples to propose their reasonable lithological classification based upon different mineral assemblages and to discuss the formation and evolution of the Ryugu parent body.

Michael E Zolensky↗
NASA NTRSDate not supplied

The NASA DEVELOP Model: Multidisciplinary Teams Conduct Interdisciplinary Projects to Produce Transdisciplinary Outcomes

The DEVELOP Program, part of NASA’s Earth Applied Sciences’ Capacity Building Program, conducts 50-70 feasibility studies each year that utilize Earth observations to address local decision-making challenges and help inform action. DEVELOP uses these projects as the mechanism to build skills in its participants and partner organizations to assess and apply satellite data insights to environmental decision-making processes. While organized by thematic focus (ex. water resource management, ecological forecasting, disaster management), projects use a multidisciplinary team approach with teams of students, recent graduates, early career professionals, and transitioning career professionals, bringing different disciplines, life experience, and perspectives to execute projects that have been collaboratively designed with end-user partner organizations (federal agencies, state and local governments, non-profit and for-profit organizations, and international organizations). Projects are interdisciplinary in nature as they integrate methods from multiple disciplines, with a focus on the incorporation of satellite data with other data sources such as socioeconomic and demographic data, in situ measurements, model outputs, and partners’ knowledge, and take place under the guidance of science advisors from NASA, academia, and other partner organizations. The culmination of these multidisciplinary teams working on projects that draw from interdisciplinary methods and approaches, is a transdisciplinary solution for the partner organizations to explore further for potential adoption. This presentation will highlight the DEVELOP model of co-production and collaboration, lessons learned integrating people and project methodologies, and impact assessment activities surrounding the program’s efforts.

Capacity Building↗
NASA NTRSDate not supplied

Artemis Internal Science Team: Mission Planning Update

As eloquently outlined in the Artemis III Science Definition Team (A3SDT) Report, the definitive statement of science priorities for the first crewed landing of the Artemis program, the return of astronauts to the surface of the Moon is expected to yield paradigm-shifting scientific advances across a wide array of scientific disciplines while facilitating the creation of a thriving cislunar economy. To help establish a cohesive management for the Artemis campaign, the NASA Science Mission Directorate (SMD) and the Exploration Systems Development Mission Directorate (ESDMD) have established an Artemis Internal Science Team to complement future competed surface geology and payload science teams while executing critical programmatic functions at the point of hardware element interface decisions. Here, we describe aspects of Artemis III mission planning, specifically the current progress towards selection of candidate exploration regions for the Artemis III mission.

Artemis↗